SAVRN
Search Contact SAVRN

Dataset · Question answering

MMLU-Pro

by TIGER-Lab TIGER-Lab/MMLU-Pro

MMLU-Pro dataset is a more robust and challenging massive multi-task understanding dataset tailored to more rigorously benchmark large language models' capabilities. This dataset contains 12K complex questions across various disciplines.

Rows12,102
Configurations1
Size4.2 MB
Licensemit
AccessPublicly accessible
Monthly Downloads246k

Dataset Card

By TIGER-Lab, published under mit, revision b189ec765aa7.

MMLU-Pro Dataset

MMLU-Pro dataset is a more robust and challenging massive multi-task understanding dataset tailored to more rigorously benchmark large language models' capabilities. This dataset contains 12K complex questions across various disciplines.

|Github | Leaderboard | Paper |

What's New

Read the full dataset card (1,124 words)

Structure

default 12,102 rows

SplitRowsSize
test12,0327.9 MB
validation7061.9 KB
question_idint64questionstringoptionslistanswerstringanswer_indexint64cot_contentstringcategorystringsrcstring

Details

Repository
TIGER-Lab/MMLU-Pro
Publisher
TIGER-Lab
Task category
Question answering
Tags
evaluation
Size category
10K<n<100K
Languages
en
Revision
b189ec765aa7ed75c8acfea42df31fdae71f97be
Last updated
2026-05-02

SAVRN's Notes on MMLU-Pro

MMLU-Pro is 12,102 questions in 4.2 MB under MIT terms, but the split layout tells you what it is: 12,032 rows of test and only 70 rows of validation. This is an evaluation set, published by TIGER-Lab as a harder, more option-dense successor to MMLU, and the near-empty validation split leaves almost no room for prompt development or calibration without touching the test data itself.

MIT licensing removes friction for commercial eval pipelines, and at 4.2 MB it costs nothing to mirror internally. The discipline that matters is contamination: this is a headline benchmark with a fixed public test split, so any model that has seen it in training will overstate capability, and reviewers increasingly check for exactly that. The page was last updated May 2026 — verify the revision when comparing scores against published results.

Files

7 files, 4.2 MB in total.

Data2 files · 4.2 MB
Documentation1 file · 11.7 KB
Other3 files · 6.3 KB
Repository1 file · 2.3 KB
Every file
FileTypeSizeSHA-256
data/test-00000-of-00001.parquetData4.1 MB0e24a191921c
data/validation-00000-of-00001.parquetData42.9 KB139423c23722
README.mdDocumentation11.7 KB—
eval.yamlOther590 B—
run_claude3.pyOther2.7 KB—
run_gpt4o.pyOther3.0 KB—
.gitattributesRepository2.3 KB—

License and Download

License
mit
Access
No access gate
Download from TIGER-Lab

Released by TIGER-Lab through its official repository on Hugging Face. Read the license.